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Ntu
Research Scientist
Research Fellow (Econometrics and Machine Learning)
On-siteSeniorResearch Scientistposted 5d ago
Role summaryAI-generated
This research fellow will develop econometric theory and machine learning methods for weak instruments and high-dimensional data, focusing on robust inference and bias correction. The role involves implementing simulations, empirical analyses, and producing reproducible code and research papers for the NTU Economics Programme.
Skills required
About this role
The Economics Programme in NTU’s School of Social Sciences seeks a Research Fellow. The research develops reliable instrumental variable (IV) estimation/inference method and machine learning algorithm with weak instruments, high-dimensional instruments or controls, and clustered data.
Key Responsibilities:
- Develop econometric theory for weak-identification-robust tests, bootstrap methods, estimator combinations, and leave-cluster-out bias correction and inference methods.
- Implement simulations and empirical analyses of import competition, education, and pretrial decisions using IV regressions.
- Prepare reproducible code, research papers, technical appendices, and presentations in collaboration with the project team.
Job Requirements:
- PhD in Economics, Econometrics, Statistics, or a closely related field by the appointment start date.
- Strong econometric theory, probability, statistics, and research skills in IV methods, causal inference, and machine learning.
- Proficiency in R, Python, MATLAB, or Julia; ability to implement simulations and analyse data.
- Strong communication and collaboration skills; specialist experience in weak identification, bootstrap methods, or cluster-robust inference is desirable.
- Entry level PhD candidates who meet the qualification requirement by the start date are welcome; prior postdoctoral experience is desirable.
We regret to inform that only shortlisted candidates will be notified.
Hiring Institution: NTUApply on Ntu →Opens in new tab
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